Hello, It took almost 2 years to develop and publish an article on this device. This is #open_source - brain-computer interface I am not sure that everybody here have access to springer library, sorry, this paper is not open-access. but technical detail in my GitHub page https://github.com/Ildaron/ironbci
So this seems to based around the Texas Instruments ADS1299 chip, which is described by TI as:
The ADS1299-4, ADS1299-6, and ADS1299 devices are a family of four-, six-, and eight-channel, low-noise, 24-bit, simultaneous-sampling delta-sigma (ΔΣ) analog-to-digital converters (ADCs) with a built-in programmable gain amplifier (PGA), internal reference, and an onboard oscillator. The ADS1299-x incorporates all commonly-required features for extracranial electroencephalogram (EEG) and electrocardiography (ECG) applications. With its high levels of integration and exceptional performance, the ADS1299-x enables the creation of scalable medical instrumentation systems at significantly reduced size, power, and overall cost.
The product page [1] further states that talks SPI with the host system (an STM32 in this project, nice).
US price for the ADS1299 on Digi-Key seems to be in the region of $50 in single-quantity.
Thanks for sharing! Did you have a look what else is needed to attempt to build this? There are some gerber files for the pcb boards + probably the components soldered on top + wires + clips + headband?
Edit: the paper actually mentions the cost of ironbci to be $350
I read some books by Nicolelis' several years ago and it seemed back then that really useful BCI's still required invasive surgery because not only do you need to gather signals from a large number of neurons you also need to be able to distinguish them (and in EEG the signals are merged together and then further obscured by the effect of the skull etc.)
It will be interesting to see how much adoption Neuralink can get with the invasive approach.
How is this effort different from what the people over at https://openbci.com/ is doing? Seems like the problem is hard enough that people should try working together as much as possible, rather than starting new, independent efforts, unless the approaches are wildly different.
The more compelling challenge is a comfortable, yet durable electrode that has good impedance without the need of gel. OpenBCI is one of a few organizations that have a good dry electrode.
Unrelated, I've been trying to think about a data store that's part of me somehow. I guess we carry our phones with us everywhere but yeah. So it's your data literally on you and accessed when connected wirelessly or by usb.
Have you heard of a flash drive lol.
The thing is this would store like your collective knowledge's/notes you've written over the years and it would be secure.
Related to this for the thought of hybrid mind/brain interface is an ideal part of it. Like thinking to control devices by looking at it.
Hi! Current neural engineering PhD candidate here. Your question is one I had early on when learning about brain modeling.
Noninvasive EEG sensors measure the synchronous activity of millions of neurons. While circuit equivalents of individual neurons are a well established idea (see Hodgkin-Huxley models for an early example), this approach does not scale to models of the full brain. There is research into using neural mass or neural field models as generative models of EEG/MEG, but those are statistical models over larger volumes of brain.
The brain is not an electric circuit. It's more like a hydraulic or osmotic circuit. Thought is powered by tiny flows of sodium ions, not flows of electricity. Specifically, sodium diffuses in blood/water much faster than charge dissipates through brain tissue.
When a lot of sodium flows into a cell (a neuron fires) it creates a positive voltage difference across the cell membrane. The concentration of sodium ions floating in the extracellular space remain essentially constant (sodium rapidly flows in from the outside area) even as the charge inside the neuron rises.
So as the neuron is at the peak of its action potential it acts like a 70 mV voltage source relative to the outside of the body. The EEG measures that voltage. It's like holding up a flourescent light near a Tesla coil[1]- electrodes closest to the neuron see a higher voltage from it, because they're measuring the ratio of resistance between 1. The electrode and neuron, through the head, and 2. the resistance to reference ground through the EEG itself. Because the head has quite high resistance (~megaohm?) EEGs require some serious input impedance.
On average neurons spend ~1 out of every ~10,000 milliseconds firing. If you had ~100 electrodes and 1 million neurons, you could triangulate to mostly work out where every single neuron is when it fires. In a human brain, there are ~billion neurons per electrode, with ~100,000 firing at any one time. EEGs are only really picking up on coordinated groups of millions of neurons firing together. Inferring where the actual neurons are is inherently a blurry guess. It is possible, but afaik (and I am very lay) most visualizations only interpolate surface potentials. Implanted electrodes can locate individual neurons, which is incredibly cool.
[+] [-] ildaron_ron|4 years ago|reply
[+] [-] vladharbuz|4 years ago|reply
I'd like to better understand why researchers are not taking more of a stand against Elsevier et al.
[+] [-] ur-whale|4 years ago|reply
Most people don't.
And many who do avoid it like the plague.
If you would like your work to gather some visibility, I would highly recommend making it available for free, eg publishing the PDF on github.
[+] [-] drdeca|4 years ago|reply
btw, it looks like there is an error with the cert for ironbci.com ? Edit: uh, I guess my phone just didn’t like that it was over http, nevermind
[+] [-] actually_a_dog|4 years ago|reply
[+] [-] unwind|4 years ago|reply
The ADS1299-4, ADS1299-6, and ADS1299 devices are a family of four-, six-, and eight-channel, low-noise, 24-bit, simultaneous-sampling delta-sigma (ΔΣ) analog-to-digital converters (ADCs) with a built-in programmable gain amplifier (PGA), internal reference, and an onboard oscillator. The ADS1299-x incorporates all commonly-required features for extracranial electroencephalogram (EEG) and electrocardiography (ECG) applications. With its high levels of integration and exceptional performance, the ADS1299-x enables the creation of scalable medical instrumentation systems at significantly reduced size, power, and overall cost.
The product page [1] further states that talks SPI with the host system (an STM32 in this project, nice).
US price for the ADS1299 on Digi-Key seems to be in the region of $50 in single-quantity.
[1] https://www.ti.com/product/ADS1299
[+] [-] Cilvic|4 years ago|reply
Edit: the paper actually mentions the cost of ironbci to be $350
[+] [-] alexgmcm|4 years ago|reply
I read some books by Nicolelis' several years ago and it seemed back then that really useful BCI's still required invasive surgery because not only do you need to gather signals from a large number of neurons you also need to be able to distinguish them (and in EEG the signals are merged together and then further obscured by the effect of the skull etc.)
It will be interesting to see how much adoption Neuralink can get with the invasive approach.
[+] [-] wrinkl3|4 years ago|reply
[+] [-] Goety|4 years ago|reply
[+] [-] einpoklum|4 years ago|reply
[+] [-] melling|4 years ago|reply
Let’s imagine a different world and maybe we’ll get it
[+] [-] guiriduro|4 years ago|reply
[+] [-] lopis|4 years ago|reply
[+] [-] capableweb|4 years ago|reply
[+] [-] beauzo|4 years ago|reply
[+] [-] jcun4128|4 years ago|reply
Have you heard of a flash drive lol.
The thing is this would store like your collective knowledge's/notes you've written over the years and it would be secure.
Related to this for the thought of hybrid mind/brain interface is an ideal part of it. Like thinking to control devices by looking at it.
[+] [-] frankish|4 years ago|reply
[+] [-] amelius|4 years ago|reply
[+] [-] minihat|4 years ago|reply
Noninvasive EEG sensors measure the synchronous activity of millions of neurons. While circuit equivalents of individual neurons are a well established idea (see Hodgkin-Huxley models for an early example), this approach does not scale to models of the full brain. There is research into using neural mass or neural field models as generative models of EEG/MEG, but those are statistical models over larger volumes of brain.
For a good overview of current efforts in EEG modeling, you might try this open access paper: https://link.springer.com/article/10.1007/s10548-021-00828-2
[+] [-] hwillis|4 years ago|reply
The brain is not an electric circuit. It's more like a hydraulic or osmotic circuit. Thought is powered by tiny flows of sodium ions, not flows of electricity. Specifically, sodium diffuses in blood/water much faster than charge dissipates through brain tissue.
When a lot of sodium flows into a cell (a neuron fires) it creates a positive voltage difference across the cell membrane. The concentration of sodium ions floating in the extracellular space remain essentially constant (sodium rapidly flows in from the outside area) even as the charge inside the neuron rises.
So as the neuron is at the peak of its action potential it acts like a 70 mV voltage source relative to the outside of the body. The EEG measures that voltage. It's like holding up a flourescent light near a Tesla coil[1]- electrodes closest to the neuron see a higher voltage from it, because they're measuring the ratio of resistance between 1. The electrode and neuron, through the head, and 2. the resistance to reference ground through the EEG itself. Because the head has quite high resistance (~megaohm?) EEGs require some serious input impedance.
On average neurons spend ~1 out of every ~10,000 milliseconds firing. If you had ~100 electrodes and 1 million neurons, you could triangulate to mostly work out where every single neuron is when it fires. In a human brain, there are ~billion neurons per electrode, with ~100,000 firing at any one time. EEGs are only really picking up on coordinated groups of millions of neurons firing together. Inferring where the actual neurons are is inherently a blurry guess. It is possible, but afaik (and I am very lay) most visualizations only interpolate surface potentials. Implanted electrodes can locate individual neurons, which is incredibly cool.
[1]: https://youtu.be/Gq03E-xHDLQ?t=57
[+] [-] ofou|4 years ago|reply
[+] [-] hwillis|4 years ago|reply
[+] [-] unknown|4 years ago|reply
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